Recent industry video compression standards adopt techniques of motion compensation, transform, quantization and entropy coding to encode video for video communication applications. Quantization is the lossy process of reducing the data bit rate to meet the bandwidth requirements of an application, but it occurs at the cost of picture quality. The information loss during the quantization process is unrecoverable, and thus the coding artifact may be introduced. Reducing the artifact distortion is an important factor in the field of noise reduction filtering.
Ringing and mosquito noise are among the worst artifacts introduced by the quantization process. They are associated with Gibb's phenomenon and are caused by the abrupt truncation of high frequency discrete cosine transform (DCT) coefficients. The ringing noise artifact is most evident along the high contrast edges in the areas of greatly smooth background. It manifests as the rippling extending outwards from the edges, and it impairs the picture quality. The mosquito noise artifact is apparent as a form of edge busyness distortion associated with movement, or a luminance/chrominance level fluctuation, close to the boundary of moving objects. Some techniques utilized to reduce the noise artifacts may involve applying a low pass filter (LPF) which can degrade picture quality.